Balancing memory utilization in a dispersed storage network

ABSTRACT

A method begins by a processing module storing a plurality of encoded data slices in a plurality of memory devices of a dispersed storage (DS) unit of a dispersed storage network (DSN) memory using a quantity load balancing function to substantially balance a quantity of encoded data slices stored within each of the plurality of memory devices, wherein data size of at least some of the plurality of encoded data slices is different. The method continues with the processing module determining whether an available memory imbalance exists between a first memory device of the plurality of memory devices and a second memory device of the plurality of memory devices. The method continues with the processing module migrating one or more encoded data slices between the first and second memory devices to reduce the available memory imbalance when the available memory imbalance exists.

CROSS REFERENCE TO RELATED PATENTS

The present U.S. Utility Patent Application claims priority pursuant to 35 U.S.C. §119(e) to the following U.S. Provisional Patent Application which is hereby incorporated herein by reference in its entirety and made part of the present U.S. Utility Patent Application for all purposes:

U.S. Provisional Patent Application Ser. No. 61/411,478, entitled “BALANCING MEMORY UTILIZATION IN A DISPERSED STORAGE NETWORK”, having a provisional filing date of Nov. 9, 2010, pending.

STATEMENT REGARDING FEDERALLY SPONSORED RESEARCH OR DEVELOPMENT

Not Applicable

INCORPORATION-BY-REFERENCE OF MATERIAL SUBMITTED ON A COMPACT DISC

Not Applicable

BACKGROUND OF THE INVENTION

1. Technical Field of the Invention

This invention relates generally to computing systems and more particularly to data storage solutions within such computing systems.

2. Description of Related Art

Computers are known to communicate, process, and store data. Such computers range from wireless smart phones to data centers that support millions of web searches, stock trades, or on-line purchases every day. In general, a computing system generates data and/or manipulates data from one form into another. For instance, an image sensor of the computing system generates raw picture data and, using an image compression program (e.g., JPEG, MPEG, etc.), the computing system manipulates the raw picture data into a standardized compressed image.

With continued advances in processing speed and communication speed, computers are capable of processing real time multimedia data for applications ranging from simple voice communications to streaming high definition video. As such, general-purpose information appliances are replacing purpose-built communications devices (e.g., a telephone). For example, smart phones can support telephony communications but they are also capable of text messaging and accessing the internet to perform functions including email, web browsing, remote applications access, and media communications (e.g., telephony voice, image transfer, music files, video files, real time video streaming. etc.).

Each type of computer is constructed and operates in accordance with one or more communication, processing, and storage standards. As a result of standardization and with advances in technology, more and more information content is being converted into digital formats. For example, more digital cameras are now being sold than film cameras, thus producing more digital pictures. As another example, web-based programming is becoming an alternative to over the air television broadcasts and/or cable broadcasts. As further examples, papers, books, video entertainment, home video, etc. are now being stored digitally, which increases the demand on the storage function of computers.

A typical computer storage system includes one or more memory devices aligned with the needs of the various operational aspects of the computer's processing and communication functions. Generally, the immediacy of access dictates what type of memory device is used. For example, random access memory (RAM) memory can be accessed in any random order with a constant response time, thus it is typically used for cache memory and main memory. By contrast, memory device technologies that require physical movement such as magnetic disks, tapes, and optical discs, have a variable response time as the physical movement can take longer than the data transfer, thus they are typically used for secondary memory (e.g., hard drive, backup memory, etc.).

A computer's storage system will be compliant with one or more computer storage standards that include, but are not limited to, network file system (NFS), flash file system (FFS), disk file system (DFS), small computer system interface (SCSI), internet small computer system interface (iSCSI), file transfer protocol (FTP), and web-based distributed authoring and versioning (WebDAV). These standards specify the data storage format (e.g., files, data objects, data blocks, directories, etc.) and interfacing between the computer's processing function and its storage system, which is a primary function of the computer's memory controller.

Despite the standardization of the computer and its storage system, memory devices fail; especially commercial grade memory devices that utilize technologies incorporating physical movement (e.g., a disc drive). For example, it is fairly common for a disc drive to routinely suffer from bit level corruption and to completely fail after three years of use. One solution is to use a higher-grade disc drive, which adds significant cost to a computer.

Another solution is to utilize multiple levels of redundant disc drives to replicate the data into two or more copies. One such redundant drive approach is called redundant array of independent discs (RAID). In a RAID device, a RAID controller adds parity data to the original data before storing it across the array. The parity data is calculated from the original data such that the failure of a disc will not result in the loss of the original data. For example, RAID 5 uses three discs to protect data from the failure of a single disc. The parity data, and associated redundancy overhead data, reduces the storage capacity of three independent discs by one third (e.g., n−1=capacity). RAID 6 can recover from a loss of two discs and requires a minimum of four discs with a storage capacity of n−2.

While RAID addresses the memory device failure issue, it is not without its own failures issues that affect its effectiveness, efficiency and security. For instance, as more discs are added to the array, the probability of a disc failure increases, which increases the demand for maintenance. For example, when a disc fails, it needs to be manually replaced before another disc fails and the data stored in the RAID device is lost. To reduce the risk of data loss, data on a RAID device is typically copied on to one or more other RAID devices. While this addresses the loss of data issue, it raises a security issue since multiple copies of data are available, which increases the chances of unauthorized access. Further, as the amount of data being stored grows, the overhead of RAID devices becomes a non-trivial efficiency issue.

BRIEF DESCRIPTION OF THE SEVERAL VIEWS OF THE DRAWING(S)

FIG. 1 is a schematic block diagram of an embodiment of a computing system in accordance with the invention;

FIG. 2 is a schematic block diagram of an embodiment of a computing core in accordance with the invention;

FIG. 3 is a schematic block diagram of an embodiment of a distributed storage processing unit in accordance with the invention;

FIG. 4 is a schematic block diagram of an embodiment of a grid module in accordance with the invention;

FIG. 5 is a diagram of an example embodiment of error coded data slice creation in accordance with the invention;

FIG. 6A is a schematic block diagram of an embodiment of a dispersed storage (DS) unit in accordance with the invention;

FIG. 6B is a diagram illustrating an example of free memory availability for a plurality of memories in accordance with the invention;

FIG. 6C is a diagram illustrating another example of free memory availability for a plurality of memories in accordance with the invention;

FIG. 6D is a diagram illustrating another example of free memory availability for a plurality of memories in accordance with the invention;

FIG. 6E is a schematic block diagram of another embodiment of a dispersed storage (DS) unit in accordance with the invention;

FIG. 6F is a flowchart illustrating an example of migrating encoded data slices in accordance with the invention;

FIG. 7A is a flowchart illustrating an example of re-assigning memories in accordance with the invention;

FIG. 7B is a flowchart illustrating an example of assigning a new memory in accordance with the invention;

FIG. 8 is a flowchart illustrating another example of migrating encoded data slices in accordance with the invention;

FIG. 9A is a flowchart illustrating an example of utilizing memory in accordance with the invention;

FIG. 9B is a flowchart illustrating an example of encoding data in accordance with the invention;

FIG. 9C is a flowchart illustrating an example of decoding encoded data slices in accordance with the invention;

FIG. 10A is a flowchart illustrating an example of validating a request in accordance with the invention; and

FIG. 10B is a flowchart illustrating an example of producing a request in accordance with the invention.

DETAILED DESCRIPTION OF THE INVENTION

FIG. 1 is a schematic block diagram of a computing system 10 that includes one or more of a first type of user devices 12, one or more of a second type of user devices 14, at least one distributed storage (DS) processing unit 16, at least one DS managing unit 18, at least one storage integrity processing unit 20, and a distributed storage network (DSN) memory 22 coupled via a network 24. The network 24 may include one or more wireless and/or wire lined communication systems; one or more private intranet systems and/or public internet systems; and/or one or more local area networks (LAN) and/or wide area networks (WAN).

The DSN memory 22 includes a plurality of distributed storage (DS) units 36 for storing data of the system. Each of the DS units 36 includes a processing module and memory and may be located at a geographically different site than the other DS units (e.g., one in Chicago, one in Milwaukee, etc.).

Each of the user devices 12-14, the DS processing unit 16, the DS managing unit 18, and the storage integrity processing unit 20 may be a portable computing device (e.g., a social networking device, a gaming device, a cell phone, a smart phone, a personal digital assistant, a digital music player, a digital video player, a laptop computer, a handheld computer, a video game controller, and/or any other portable device that includes a computing core) and/or a fixed computing device (e.g., a personal computer, a computer server, a cable set-top box, a satellite receiver, a television set, a printer, a fax machine, home entertainment equipment, a video game console, and/or any type of home or office computing equipment). Such a portable or fixed computing device includes a computing core 26 and one or more interfaces 30, 32, and/or 33. An embodiment of the computing core 26 will be described with reference to FIG. 2.

With respect to the interfaces, each of the interfaces 30, 32, and 33 includes software and/or hardware to support one or more communication links via the network 24 indirectly and/or directly. For example, interfaces 30 support a communication link (wired, wireless, direct, via a LAN, via the network 24, etc.) between the first type of user device 14 and the DS processing unit 16. As another example, DSN interface 32 supports a plurality of communication links via the network 24 between the DSN memory 22 and the DS processing unit 16, the first type of user device 12, and/or the storage integrity processing unit 20. As yet another example, interface 33 supports a communication link between the DS managing unit 18 and any one of the other devices and/or units 12, 14, 16, 20, and/or 22 via the network 24.

In general and with respect to data storage, the system 10 supports three primary functions: distributed network data storage management, distributed data storage and retrieval, and data storage integrity verification. In accordance with these three primary functions, data can be distributedly stored in a plurality of physically different locations and subsequently retrieved in a reliable and secure manner regardless of failures of individual storage devices, failures of network equipment, the duration of storage, the amount of data being stored, attempts at hacking the data, etc.

The DS managing unit 18 performs distributed network data storage management functions, which include establishing distributed data storage parameters, performing network operations, performing network administration, and/or performing network maintenance. The DS managing unit 18 establishes the distributed data storage parameters (e.g., allocation of virtual DSN memory space, distributed storage parameters, security parameters, billing information, user profile information, etc.) for one or more of the user devices 12-14 (e.g., established for individual devices, established for a user group of devices, established for public access by the user devices, etc.). For example, the DS managing unit 18 coordinates the creation of a vault (e.g., a virtual memory block) within the DSN memory 22 for a user device (for a group of devices, or for public access). The DS managing unit 18 also determines the distributed data storage parameters for the vault. In particular, the DS managing unit 18 determines a number of slices (e.g., the number that a data segment of a data file and/or data block is partitioned into for distributed storage) and a read threshold value (e.g., the minimum number of slices required to reconstruct the data segment).

As another example, the DS managing module 18 creates and stores, locally or within the DSN memory 22, user profile information. The user profile information includes one or more of authentication information, permissions, and/or the security parameters. The security parameters may include one or more of encryption/decryption scheme, one or more encryption keys, key generation scheme, and data encoding/decoding scheme.

As yet another example, the DS managing unit 18 creates billing information for a particular user, user group, vault access, public vault access, etc. For instance, the DS managing unit 18 tracks the number of times user accesses a private vault and/or public vaults, which can be used to generate a per-access bill. In another instance, the DS managing unit 18 tracks the amount of data stored and/or retrieved by a user device and/or a user group, which can be used to generate a per-data-amount bill.

The DS managing unit 18 also performs network operations, network administration, and/or network maintenance. As at least part of performing the network operations and/or administration, the DS managing unit 18 monitors performance of the devices and/or units of the system 10 for potential failures, determines the devices and/or unit's activation status, determines the devices' and/or units' loading, and any other system level operation that affects the performance level of the system 10. For example, the DS managing unit 18 receives and aggregates network management alarms, alerts, errors, status information, performance information, and messages from the devices 12-14 and/or the units 16, 20, 22. For example, the DS managing unit 18 receives a simple network management protocol (SNMP) message regarding the status of the DS processing unit 16.

The DS managing unit 18 performs the network maintenance by identifying equipment within the system 10 that needs replacing, upgrading, repairing, and/or expanding. For example, the DS managing unit 18 determines that the DSN memory 22 needs more DS units 36 or that one or more of the DS units 36 needs updating.

The second primary function (i.e., distributed data storage and retrieval) begins and ends with a user device 12-14. For instance, if a second type of user device 14 has a data file 38 and/or data block 40 to store in the DSN memory 22, it send the data file 38 and/or data block 40 to the DS processing unit 16 via its interface 30. As will be described in greater detail with reference to FIG. 2, the interface 30 functions to mimic a conventional operating system (OS) file system interface (e.g., network file system (NFS), flash file system (FFS), disk file system (DFS), file transfer protocol (FTP), web-based distributed authoring and versioning (WebDAV), etc.) and/or a block memory interface (e.g., small computer system interface (SCSI), internet small computer system interface (iSCSI), etc.). In addition, the interface 30 may attach a user identification code (ID) to the data file 38 and/or data block 40.

The DS processing unit 16 receives the data file 38 and/or data block 40 via its interface 30 and performs a distributed storage (DS) process 34 thereon (e.g., an error coding dispersal storage function). The DS processing 34 begins by partitioning the data file 38 and/or data block 40 into one or more data segments, which is represented as Y data segments. For example, the DS processing 34 may partition the data file 38 and/or data block 40 into a fixed byte size segment (e.g., 2¹ to 2^(n) bytes, where n=>2) or a variable byte size (e.g., change byte size from segment to segment, or from groups of segments to groups of segments, etc.).

For each of the Y data segments, the DS processing 34 error encodes (e.g., forward error correction (FEC), information dispersal algorithm, or error correction coding) and slices (or slices then error encodes) the data segment into a plurality of error coded (EC) data slices 42-48, which is represented as X slices per data segment. The number of slices (X) per segment, which corresponds to a number of pillars n, is set in accordance with the distributed data storage parameters and the error coding scheme. For example, if a Reed-Solomon (or other FEC scheme) is used in an n/k system, then a data segment is divided into n slices, where k number of slices is needed to reconstruct the original data (i.e., k is the threshold). As a few specific examples, the n/k factor may be 5/3; 6/4; 8/6; 8/5; 16/10.

For each slice 42-48, the DS processing unit 16 creates a unique slice name and appends it to the corresponding slice 42-48. The slice name includes universal DSN memory addressing routing information (e.g., virtual memory addresses in the DSN memory 22) and user-specific information (e.g., user ID, file name, data block identifier, etc.).

The DS processing unit 16 transmits the plurality of EC slices 42-48 to a plurality of DS units 36 of the DSN memory 22 via the DSN interface 32 and the network 24. The DSN interface 32 formats each of the slices for transmission via the network 24. For example, the DSN interface 32 may utilize an internet protocol (e.g., TCP/IP, etc.) to packetize the slices 42-48 for transmission via the network 24.

The number of DS units 36 receiving the slices 42-48 is dependent on the distributed data storage parameters established by the DS managing unit 18. For example, the DS managing unit 18 may indicate that each slice is to be stored in a different DS unit 36. As another example, the DS managing unit 18 may indicate that like slice numbers of different data segments are to be stored in the same DS unit 36. For example, the first slice of each of the data segments is to be stored in a first DS unit 36, the second slice of each of the data segments is to be stored in a second DS unit 36, etc. In this manner, the data is encoded and distributedly stored at physically diverse locations to improved data storage integrity and security. Further examples of encoding the data segments will be provided with reference to one or more of FIGS. 2-10B.

Each DS unit 36 that receives a slice 42-48 for storage translates the virtual DSN memory address of the slice into a local physical address for storage. Accordingly, each DS unit 36 maintains a virtual to physical memory mapping to assist in the storage and retrieval of data.

The first type of user device 12 performs a similar function to store data in the DSN memory 22 with the exception that it includes the DS processing. As such, the device 12 encodes and slices the data file and/or data block it has to store. The device then transmits the slices 11 to the DSN memory via its DSN interface 32 and the network 24.

For a second type of user device 14 to retrieve a data file or data block from memory, it issues a read command via its interface 30 to the DS processing unit 16. The DS processing unit 16 performs the DS processing 34 to identify the DS units 36 storing the slices of the data file and/or data block based on the read command. The DS processing unit 16 may also communicate with the DS managing unit 18 to verify that the user device 14 is authorized to access the requested data.

Assuming that the user device is authorized to access the requested data, the DS processing unit 16 issues slice read commands to at least a threshold number of the DS units 36 storing the requested data (e.g., to at least 10 DS units for a 16/10 error coding scheme). Each of the DS units 36 receiving the slice read command, verifies the command, accesses its virtual to physical memory mapping, retrieves the requested slice, or slices, and transmits it to the DS processing unit 16.

Once the DS processing unit 16 has received a read threshold number of slices for a data segment, it performs an error decoding function and de-slicing to reconstruct the data segment. When Y number of data segments has been reconstructed, the DS processing unit 16 provides the data file 38 and/or data block 40 to the user device 14. Note that the first type of user device 12 performs a similar process to retrieve a data file and/or data block.

The storage integrity processing unit 20 performs the third primary function of data storage integrity verification. In general, the storage integrity processing unit 20 periodically retrieves slices 45, and/or slice names, of a data file or data block of a user device to verify that one or more slices have not been corrupted or lost (e.g., the DS unit failed). The retrieval process mimics the read process previously described.

If the storage integrity processing unit 20 determines that one or more slices is corrupted or lost, it rebuilds the corrupted or lost slice(s) in accordance with the error coding scheme. The storage integrity processing unit 20 stores the rebuild slice, or slices, in the appropriate DS unit(s) 36 in a manner that mimics the write process previously described.

FIG. 2 is a schematic block diagram of an embodiment of a computing core 26 that includes a processing module 50, a memory controller 52, main memory 54, a video graphics processing unit 55, an input/output (IO) controller 56, a peripheral component interconnect (PCI) interface 58, at least one IO device interface module 62, a read only memory (ROM) basic input output system (BIOS) 64, and one or more memory interface modules. The memory interface module(s) includes one or more of a universal serial bus (USB) interface module 66, a host bus adapter (HBA) interface module 68, a network interface module 70, a flash interface module 72, a hard drive interface module 74, and a DSN interface module 76. Note the DSN interface module 76 and/or the network interface module 70 may function as the interface 30 of the user device 14 of FIG. 1. Further note that the IO device interface module 62 and/or the memory interface modules may be collectively or individually referred to as IO ports.

FIG. 3 is a schematic block diagram of an embodiment of a dispersed storage (DS) processing module 34 of user device 12 and/or of the DS processing unit 16. The DS processing module 34 includes a gateway module 78, an access module 80, a grid module 82, and a storage module 84. The DS processing module 34 may also include an interface 30 and the DSnet interface 32 or the interfaces 68 and/or 70 may be part of user 12 or of the DS processing unit 14. The DS processing module 34 may further include a bypass/feedback path between the storage module 84 to the gateway module 78. Note that the modules 78-84 of the DS processing module 34 may be in a single unit or distributed across multiple units.

In an example of storing data, the gateway module 78 receives an incoming data object that includes a user ID field 86, an object name field 88, and the data field 40 and may also receive corresponding information that includes a process identifier (e.g., an internal process/application ID), metadata, a file system directory, a block number, a transaction message, a user device identity (ID), a data object identifier, a source name, and/or user information. The gateway module 78 authenticates the user associated with the data object by verifying the user ID 86 with the managing unit 18 and/or another authenticating unit.

When the user is authenticated, the gateway module 78 obtains user information from the management unit 18, the user device, and/or the other authenticating unit. The user information includes a vault identifier, operational parameters, and user attributes (e.g., user data, billing information, etc.). A vault identifier identifies a vault, which is a virtual memory space that maps to a set of DS storage units 36. For example, vault 1 (i.e., user 1's DSN memory space) includes eight DS storage units (X=8 wide) and vault 2 (i.e., user 2's DSN memory space) includes sixteen DS storage units (X=16 wide). The operational parameters may include an error coding algorithm, the width n (number of pillars X or slices per segment for this vault), a read threshold T, a write threshold, an encryption algorithm, a slicing parameter, a compression algorithm, an integrity check method, caching settings, parallelism settings, and/or other parameters that may be used to access the DSN memory layer.

The gateway module 78 uses the user information to assign a source name 35 to the data. For instance, the gateway module 60 determines the source name 35 of the data object 40 based on the vault identifier and the data object. For example, the source name may contain a file identifier (ID), a vault generation number, a reserved field, and a vault identifier (ID). As another example, the gateway module 78 may generate the file ID based on a hash function of the data object 40. Note that the gateway module 78 may also perform message conversion, protocol conversion, electrical conversion, optical conversion, access control, user identification, user information retrieval, traffic monitoring, statistics generation, configuration, management, and/or source name determination.

The access module 80 receives the data object 40 and creates a series of data segments 1 through Y 90-92 in accordance with a data storage protocol (e.g., file storage system, a block storage system, and/or an aggregated block storage system). The number of segments Y may be chosen or randomly assigned based on a selected segment size and the size of the data object. For example, if the number of segments is chosen to be a fixed number, then the size of the segments varies as a function of the size of the data object. For instance, if the data object is an image file of 4,194,304 eight bit bytes (e.g., 33,554,432 bits) and the number of segments Y=131,072, then each segment is 256 bits or 32 bytes. As another example, if segment sized is fixed, then the number of segments Y varies based on the size of data object. For instance, if the data object is an image file of 4,194,304 bytes and the fixed size of each segment is 4,096 bytes, the then number of segments Y=1,024. Note that each segment is associated with the same source name.

The grid module 82 receives the data segments and may manipulate (e.g., compression, encryption, cyclic redundancy check (CRC), etc.) each of the data segments before performing an error coding function of the error coding dispersal storage function to produce a pre-manipulated data segment. After manipulating a data segment, if applicable, the grid module 82 error encodes (e.g., Reed-Solomon, Convolution encoding, Trellis encoding, etc.) the data segment or manipulated data segment into X error coded data slices 42-44.

The value X, or the number of pillars (e.g., X=16), is chosen as a parameter of the error coding dispersal storage function. Other parameters of the error coding dispersal function include a read threshold T, a write threshold W, etc. The read threshold (e.g., T=10, when X=16) corresponds to the minimum number of error-free error coded data slices required to reconstruct the data segment. In other words, the DS processing module 34 can compensate for X-T (e.g., 16−10 =6) missing error coded data slices per data segment. The write threshold W corresponds to a minimum number of DS storage units that acknowledge proper storage of their respective data slices before the DS processing module indicates proper storage of the encoded data segment. Note that the write threshold is greater than or equal to the read threshold for a given number of pillars (X).

For each data slice of a data segment, the grid module 82 generates a unique slice name 37 and attaches it thereto. The slice name 37 includes a universal routing information field and a vault specific field and may be 48 bytes (e.g., 24 bytes for each of the universal routing information field and the vault specific field). As illustrated, the universal routing information field includes a slice index, a vault ID, a vault generation, and a reserved field. The slice index is based on the pillar number and the vault ID and, as such, is unique for each pillar (e.g., slices of the same pillar for the same vault for any segment will share the same slice index). The vault specific field includes a data name, which includes a file ID and a segment number (e.g., a sequential numbering of data segments 1-Y of a simple data object or a data block number).

Prior to outputting the error coded data slices of a data segment, the grid module may perform post-slice manipulation on the slices. If enabled, the manipulation includes slice level compression, encryption, CRC, addressing, tagging, and/or other manipulation to improve the effectiveness of the computing system.

When the error coded data slices of a data segment are ready to be outputted, the grid module 82 determines which of the DS storage units 36 will store the EC data slices based on a dispersed storage memory mapping associated with the user's vault and/or DS storage unit attributes. The DS storage unit attributes may include availability, self-selection, performance history, link speed, link latency, ownership, available DSN memory, domain, cost, a prioritization scheme, a centralized selection message from another source, a lookup table, data ownership, and/or any other factor to optimize the operation of the computing system. Note that the number of DS storage units 36 is equal to or greater than the number of pillars (e.g., X) so that no more than one error coded data slice of the same data segment is stored on the same DS storage unit 36. Further note that EC data slices of the same pillar number but of different segments (e.g., EC data slice 1 of data segment 1 and EC data slice 1 of data segment 2) may be stored on the same or different DS storage units 36.

The storage module 84 performs an integrity check on the outbound encoded data slices and, when successful, identifies a plurality of DS storage units based on information provided by the grid module 82. The storage module 84 then outputs the encoded data slices 1 through X of each segment 1 through Y to the DS storage units 36. Each of the DS storage units 36 stores its EC data slice(s) and maintains a local virtual DSN address to physical location table to convert the virtual DSN address of the EC data slice(s) into physical storage addresses.

In an example of a read operation, the user device 12 and/or 14 sends a read request to the DS processing unit 14, which authenticates the request. When the request is authentic, the DS processing unit 14 sends a read message to each of the DS storage units 36 storing slices of the data object being read. The slices are received via the DSnet interface 32 and processed by the storage module 84, which performs a parity check and provides the slices to the grid module 82 when the parity check was successful. The grid module 82 decodes the slices in accordance with the error coding dispersal storage function to reconstruct the data segment. The access module 80 reconstructs the data object from the data segments and the gateway module 78 formats the data object for transmission to the user device.

FIG. 4 is a schematic block diagram of an embodiment of a grid module 82 that includes a control unit 73, a pre-slice manipulator 75, an encoder 77, a slicer 79, a post-slice manipulator 81, a pre-slice de-manipulator 83, a decoder 85, a de-slicer 87, and/or a post-slice de-manipulator 89. Note that the control unit 73 may be partially or completely external to the grid module 82. For example, the control unit 73 may be part of the computing core at a remote location, part of a user device, part of the DS managing unit 18, or distributed amongst one or more DS storage units.

In an example of write operation, the pre-slice manipulator 75 receives a data segment 90-92 and a write instruction from an authorized user device. The pre-slice manipulator 75 determines if pre-manipulation of the data segment 90-92 is required and, if so, what type. The pre-slice manipulator 75 may make the determination independently or based on instructions from the control unit 73, where the determination is based on a computing system-wide predetermination, a table lookup, vault parameters associated with the user identification, the type of data, security requirements, available DSN memory, performance requirements, and/or other metadata.

Once a positive determination is made, the pre-slice manipulator 75 manipulates the data segment 90-92 in accordance with the type of manipulation. For example, the type of manipulation may be compression (e.g., Lempel-Ziv-Welch, Huffman, Golomb, fractal, wavelet, etc.), signatures (e.g., Digital Signature Algorithm (DSA), Elliptic Curve DSA, Secure Hash Algorithm, etc.), watermarking, tagging, encryption (e.g., Data Encryption Standard, Advanced Encryption Standard, etc.), adding metadata (e.g., time/date stamping, user information, file type, etc.), cyclic redundancy check (e.g., CRC32), and/or other data manipulations to produce the pre-manipulated data segment.

The encoder 77 encodes the pre-manipulated data segment 92 using a forward error correction (FEC) encoder (and/or other type of erasure coding and/or error coding) to produce an encoded data segment 94. The encoder 77 determines which forward error correction algorithm to use based on a predetermination associated with the user's vault, a time based algorithm, user direction, DS managing unit direction, control unit direction, as a function of the data type, as a function of the data segment 92 metadata, and/or any other factor to determine algorithm type. The forward error correction algorithm may be Golay, Multidimensional parity, Reed-Solomon, Hamming, Bose Ray Chauduri Hocquenghem (BCH), Cauchy-Reed-Solomon, or any other FEC encoder. Note that the encoder 77 may use a different encoding algorithm for each data segment 92, the same encoding algorithm for the data segments 92 of a data object, or a combination thereof.

The encoded data segment 94 is of greater size than the data segment 92 by the overhead rate of the encoding algorithm by a factor of X/T, where X is the width or number of slices, and T is the read threshold. In this regard, the corresponding decoding process can accommodate at most X-T missing EC data slices and still recreate the data segment 92. For example, if X=16 and T=10, then the data segment 92 will be recoverable as long as 10 or more EC data slices per segment are not corrupted.

The slicer 79 transforms the encoded data segment 94 into EC data slices in accordance with the slicing parameter from the vault for this user and/or data segment 92. For example, if the slicing parameter is X=16, then the slicer 79 slices each encoded data segment 94 into 16 encoded slices.

The post-slice manipulator 81 performs, if enabled, post-manipulation on the encoded slices to produce the EC data slices. If enabled, the post-slice manipulator 81 determines the type of post-manipulation, which may be based on a computing system-wide predetermination, parameters in the vault for this user, a table lookup, the user identification, the type of data, security requirements, available DSN memory, performance requirements, control unit directed, and/or other metadata. Note that the type of post-slice manipulation may include slice level compression, signatures, encryption, CRC, addressing, watermarking, tagging, adding metadata, and/or other manipulation to improve the effectiveness of the computing system.

In an example of a read operation, the post-slice de-manipulator 89 receives at least a read threshold number of EC data slices and performs the inverse function of the post-slice manipulator 81 to produce a plurality of encoded slices. The de-slicer 87 de-slices the encoded slices to produce an encoded data segment 94. The decoder 85 performs the inverse function of the encoder 77 to recapture the data segment 90-92. The pre-slice de-manipulator 83 performs the inverse function of the pre-slice manipulator 75 to recapture the data segment 90-92.

FIG. 5 is a diagram of an example of slicing an encoded data segment 94 by the slicer 79. In this example, the encoded data segment 94 includes thirty-two bits, but may include more or less bits. The slicer 79 disperses the bits of the encoded data segment 94 across the EC data slices in a pattern as shown. As such, each EC data slice does not include consecutive bits of the data segment 94 reducing the impact of consecutive bit failures on data recovery. For example, if EC data slice 2 (which includes bits 1, 5, 9, 13, 17, 25, and 29) is unavailable (e.g., lost, inaccessible, or corrupted), the data segment can be reconstructed from the other EC data slices (e.g., 1, 3 and 4 for a read threshold of 3 and a width of 4).

FIG. 6A is a schematic block diagram of an embodiment of a dispersed storage (DS) unit 36. The DS unit 36 includes a dispersed storage network (DSN) interface 32, a control module 104, a configuration memory 102, and a plurality of memories A-E. The control module may be implemented as logic in a computing core 26 and/or as a software algorithm operating on a computing core 26. A processing module of the control module may execute a method to control the plurality of memories A-E, stored encoded data slices in the plurality of memories A-E, retrieve encoded data slices from the plurality of memories, and utilize the configuration memory as a repository for configuration information (e.g., virtual DSN addressing range assignments for each of the memories) associated with the DS unit. Such a method is described in greater detail with reference to FIGS. 6B-6F. The configuration memory 102 and each memory of the plurality of memories A-E may be a read-only memory, random access memory, volatile memory, non-volatile memory, static memory, dynamic memory, flash memory, magnetic disk drive memory, solid state memory, cache memory, and/or any device that stores digital information. For example, the configuration memory 102 is implemented utilizing a solid-state flash memory and each of the plurality of memories A-E are implemented utilizing a magnetic disk drive memory.

As an example of initialization operation, the control module 104 receives a virtual DSN address range assignment message that includes an overall address range assignment for the DS unit 36. The control module 104 determines available memories as memories A-E based on one or more of configuration information retrieved from the configuration memory 102, an installation indicator, a query, and a message. The control module 104 determines subdivisions of the address range to assign to each of the plurality of memories A-E. For instance, the control module assigns address range 101-200 to memory A, address range 201-300 to memory B, address range 301-400 to memory C, address range 401-500 to memory D, and address range 501-600 to memory A when the overall address range assignment is 101-600. In such an instance, contiguous address ranges are assigned to the plurality of memories such that there are no gaps in address ranges. In the instance, each memory is assigned a uniform number of addresses within an address range assignment when an expected address range utilization is of a uniform nature. As another instance, the control module 104 assigns non-uniform address ranges to each of the memories A-E when the expected address range utilization is of a non-uniform nature. The control module 104 stores address range assignment information as configuration information in the configuration memory 102 (e.g., address range assignments by memory).

As an example of storage operation, the control module 104 receives a storage request via the DSN interface 32, wherein the request includes an encoded data slice and slice name. The control module 104 retrieves configuration information from the configuration memory 102. The control module 104 determines an assigned memory based on the slice name and the configuration information such that the slice name address falls within an address range associated with the assigned memory. The control module 104 stores the encoded data slice in the assigned memory and updates the configuration information with the slice name. Note that a memory of the plurality of memories A-E may be utilized to store more data slices than other memories when the slice names of successive storage requests fall within an address range associated with the memory. Note that an amount of available free space of each of the memories may vary over time. A memory utilization balancing method is discussed in greater detail with reference to FIGS. 6B-6F.

FIG. 6B is a diagram illustrating an example of free memory (e.g., available memory) availability for a plurality of memories. For example, the plurality of memories A-E may be implemented in a single dispersed storage (DS) unit. As another example, the plurality of memories A-E may be implemented in two or more DS units. As illustrated, memory A is 60% free (e.g., not utilized), memory B is 50% free, memory C is 30% free, memory D is 45% free, and memory E is 40% free. In such an example, memory C may have been utilized more often than other memories for data storage operations as memory C has a least amount of free space.

A rebalancing method may provide a memory utilization improvement wherein encoded data slices are migrated between one or more memories. Such a rebalancing method may determine how to migrate encoded data slices based on calculating a migration score for pairs of memories. For example, the migration score may be calculated as migration score (first memory, second memory)=|first memory free space—second memory free space|/min (first memory free space, second memory free space). For instance, migration score (memory A, memory B)=0.2, migration score (memory B, memory C)=0.667, migration score (memory C, memory D)=0.5, migration score (memory D, memory E)=0.125 based on memory free space for memories A-E as illustrated in FIG. 6B. Next, the migration score is compared to a migration threshold to determine whether the comparison is favorable. For example, the comparison is not favorable when the migration score of a memory pair is greater than migration threshold. For instance, the comparison is not favorable when the migration score (memory B, memory C)=0.667 and the migration threshold is 0.5. Alternatively, a memory pair may be selected for migration when an associated migration score is the highest of each migration score of the consecutive memory pairs. Next, encoded data slices may be moved from a memory with the least amount of free space of the memory pair to the other memory of the memory pair. For instance, encoded data slices may be moved from memory C to memory B to balance the memory utilization. Next, a configuration information update may indicate updated virtual dispersed storage network (DSN) address range assignments for the rebalanced memories such that the slice names of the encoded data slices that are associated with corresponding memories (e.g., where they are stored). The method to migrate encoded data slices is discussed in greater detail with reference to FIG. 6F.

FIG. 6C is a diagram illustrating another example of free memory availability for a plurality of memories subsequent to an encoded data slice migration as previously discussed with reference to FIG. 6B. As illustrated, memory A is 60% free memory B is 40% free, memory C is 40% free, memory D is 45% free, and memory E is 40% free. Note that memory B and memory C have 40% free as a result of rebalancing such a memory pair. The example continues such that a migration score may be calculated for each consecutive memory pair of the plurality of memories. For instance, migration score (memory A, memory B)=0.5, migration score (memory B, memory C)=0.0, migration score (memory C, memory D)=0.125, migration score (memory D, memory E)=0.125 based on memory free space for memories A-E as illustrated in FIG. 6C. As an example of rebalancing, a memory pair of memory A and memory B is selected for rebalancing based on that memory pair having a highest migration score=0.5 of the memory pairs.

As alternative example, the memory pair of memory A and memory B is selected for rebalancing based on the migration score of 0.5 being greater than a migration threshold when the migration threshold is 0.4. Next, encoded data slices are migrated from a memory with the least amount of free space of the memory pair to the other memory of the memory pair. For instance, encoded data slices are moved from memory B to memory A to balance the memory utilization. Next, a configuration information update indicates updated virtual dispersed storage network (DSN) address range assignments for the rebalanced memories such that the slice names of the encoded data slices that are associated with corresponding memories (e.g., where they are stored).

FIG. 6D is a diagram illustrating another example of free memory availability for a plurality of memories subsequent to an encoded data slice migration as previously discussed with reference to FIG. 6C. As illustrated, memory A is 50% free memory B is 50% free, memory C is 40% free, memory D is 45% free, and memory E is 40% free. Note that memory A and memory B have 50% free as a result of rebalancing such a memory pair. The example continues such that a migration score may be calculated for each consecutive memory pair of the plurality of memories (e.g., as previously discussed). For instance, migration score (memory A, memory B)=0.0, migration score (memory B, memory C)=0.25, migration score (memory C, memory D)=0.125, migration score (memory D, memory E)=0.125 based on memory free space for memories A-E as illustrated in FIG. 6D. As example of rebalancing, a memory pair of memory B and memory C is chosen for rebalancing based on that memory pair having a highest migration score=0.25 of the memory pairs.

As an alternative example, the memory pair of memory B and memory C is chosen for rebalancing based on the migration score of 0.25 being greater than a migration threshold when the migration threshold is 0.2. Next, encoded data slices are migrated from a memory with the least amount of free space of the memory pair to the other memory of the memory pair. For instance, encoded data slices are migrated from memory B to memory C to balance the memory utilization. Next, a configuration information update indicates updated virtual dispersed storage network (DSN) address range assignments for the rebalanced memories such that the slice names of the encoded data slices that are associated with corresponding memories (e.g., where they are stored).

FIG. 6E is a schematic block diagram of another embodiment of a dispersed storage (DS) unit. The DS unit 36 includes a dispersed storage network (DSN) interface 32, a control module 104, a configuration memory 102, and a plurality of memory devices A-E. The control module 104 includes a selector 106 to route a selected encoded data slice from a plurality of received encoded data slices to a selected memory of the memories A-E. The selected slice may be routed to the selected memory in accordance with at least one of a slice name addressing approach and a quantity load balancing function. The control module 104 determines the selected memory based on a slice name associated with the encoded data slice when the slice name addressing approach is utilized.

The control module 104 stores a plurality of encoded data slices in the plurality of memory devices A-E of a dispersed storage (DS) unit of a dispersed storage network (DSN) memory using the quantity load balancing function when the quantity load balancing function is utilized. The control module 104 stores the plurality of encoded data slices in the plurality of memory devices A-E using the quantity load balancing function to substantially balance a quantity of encoded data slices stored within each of the plurality of memory devices, wherein data size of at least some of the plurality of encoded data slices is different. The quantity load balancing includes at least one of a round robin even distribution approach by quantity of encoded data slices, an uneven distribution approach by quantity of encoded data slices (e.g., 2 slices to memory A for every 1 slice to memories B-E), and a skipping distribution approach by quantity of encoded data slices (e.g., 1 slice to memory A, no slices to memory B, and 1 slice to memories C-E).

As an example of operation, the DSN interface 32 receives encoded data slices 1-10. The DSN interface 32 forwards the encoded data slices 1-10 to the control module 104. The control module 104 determines the quantity load balancing function to include the round robin scheme of storage of the encoded data slices 1-10 evenly amongst the plurality of memory devices A-E based on a predetermination. The control module 104 controls the selector 106 to route the encoded data slice 1 to memory A, encoded data slice 2 to memory B, encoded data slice 3 to memory C, encoded data slice 4 to memory D, encoded data slice 5 to memory E, encoded data slice 6 to memory A, encoded data slice 7 to memory B, encoded data slice 8 to memory C, encoded data slice 9 to memory D, and encoded data slice 10 to memory E.

FIG. 6F is a flowchart illustrating an example of migrating encoded data slices. The method begins with step 110 where a processing module (e.g., of a dispersed storage (DS) unit) stores a plurality of encoded data slices in a plurality of memory devices of a dispersed storage (DS) unit of a dispersed storage network (DSN) memory using a quantity load balancing function to substantially balance a quantity of encoded data slices stored within each of the plurality of memory devices, wherein data size of at least some of the plurality of encoded data slices is different.

The method continues at step 112 where the processing module determines whether an available memory imbalance exists between a first memory device of the plurality of memory devices and a second memory device of the plurality of memory devices. The determining whether the available memory imbalance exists includes determining an available memory value of the first memory device, determining an available memory value of the second memory device, determining a difference available memory value based on the available memory values of the first and second memory device, comparing the difference available memory value with an available memory differential threshold, and when the comparing the difference available memory value with the available memory differential threshold is unfavorable, indicating that the available memory imbalance exists. The available memory differential threshold may be very low such that any difference triggers a migration.

The determining the difference available memory value includes at least one of subtracting the available memory value of the first memory device from the available memory value of the second memory device to produce the difference available memory value and calculating a migration score based on a subtraction of the available memory value of the first memory device from the available memory value of the second memory device to produce an available memory resultant value and dividing the available memory resultant value from one of the available memory value of the first memory device and the available memory value of the second memory device. For example, the processing module may determine the migration score in accordance with a formula of: migration score=|the first memory availability level—the second memory availability level|/min (the first memory availability level, the second memory availability level).

The method continues at step 114, when the available memory imbalance exists, where the processing module migrates one or more encoded data slices between the first and second memory devices to reduce the available memory imbalance. The migrating the one or more encoded data slices between the first and second memory devices includes, when the available memory imbalance exists because an available memory value of the first memory device is less than an available memory value of the second memory device, selecting the one or more encoded data slices associated with the first memory for migration to produce a migration set of encoded data slices, retrieving the migration set of encoded data slices from the first memory, storing the migration set of encoded data slices in the second memory, modifying a first set of DSN addresses associated with the first memory device to produce a modified first set of DSN addresses, and modifying a second set of DSN addresses associated with the second memory device to produce a modified second set of DSN addresses.

The selecting the one or more encoded data slices includes determining a magnitude of the available memory imbalance, determining data size of the one or more encoded data slices, and selecting the one or more encoded data slices based on the magnitude of the available memory imbalance and the data size of the one or more encoded data slices. Alternatively, the selecting the one or more encoded data slices includes at least one of identifying encoded data slices based on an encoded data slice priority level and identifying encoded data slices based on an encoded data slice type indicator.

The method continues at step 116 where the processing module updates a slice location table based on the migrating the one or more encoded data slices between the first and second memory devices. The modifying the first set of DSN addresses to produce the modified first set of DSN addresses includes modifying the first set of DSN addresses to exclude DSN addresses associated with the migration set of encoded data slices. The modifying the second set of DSN addresses to produce the modified second set of DSN addresses includes modifying the second set of DSN addresses to include DSN addresses associated with the migration set of encoded data slices.

The method continues at step 118 where the processing module determines whether a second available memory imbalance exists between a third memory device of the plurality of memory devices and a fourth memory device of the plurality of memory devices. The method continues at step 120, when the second available memory imbalance exists, where the processing module migrates another one or more encoded data slices between the third and fourth memory devices to reduce the available memory imbalance.

The method continues at step 122 where the processing module compares the available memory imbalance with the second available memory imbalance and prioritizes the migrating of the one or more encoded data slices between the first and second memory devices and the migrating of the other one or more encoded data slices between the third and fourth memory devices based on the comparing. For example, the processing module prioritizes migrating the other one or more encoded data slices between the third and fourth memory devices when the second available memory imbalance includes an imbalance that is greater than the imbalance of the available memory imbalance. Alternatively, processing module considers imbalances of all possible pairings of memory devices to prioritize encoded data slice migration.

FIG. 7A is a flowchart illustrating an example of re-assigning memories. The method begins with step 124 where a processing module (e.g., of a dispersed storage (DS) unit) identifies an out of service memory. The identification may be based on one or more of a failed memory indicator, a memory removal indicator, a maintenance schedule, a downtime schedule, a power-down schedule, a power savings indicator, a management input, an error rate history, a memory device type, a memory manufacturer indicator, a memory size indicator, and a bandwidth utilization indicator. For example, the processing module identifies the out of service memory when the processing module receives the failed memory indicator. As another example, the processing module identifies the out of service memory when the processing module receives the memory removal indicator.

The method continues at step 126 where the processing module determines an out of service memory dispersed storage network (DSN) address range assignment. The determination may be based on one or more of the out of service memory, a virtual DSN address to physical location table lookup, a message, and a list. For example, the processing module utilizes an identifier associated with the out of service memory to index in the virtual DSN address to physical location table to determine the address range assignment of the out of service memory.

The method continues at step 128 where the processing module determines adjacent memories. Note that adjacent memories includes memories that are adjacent with respect to a virtual dispersed storage network (DSN) addresses. The determination may be based on one or more of the out of service memory, the out of service memory DSN address range assignment, a virtual DSN address to physical location table lookup, a message, and a list. For example, the processing module retrieves identities of the adjacent memories associated with address ranges above and below the address range of the out of service memory from the virtual DSN address to physical location table. The method continues at step 130 where the processing module determines adjacent memories DSN address range assignments (e.g., based on a virtual DSN address to physical location table lookup).

The method continues at step 132 where the processing module determines a DSN address range re-assignment approach. The re-assignment approach may include how much encoded data slice storage of the out of service memory to assign to the adjacent memories (e.g., evenly, in proportion to free space, per a predetermination). The determination may be based on one or more of adjacent memory free space, a re-assigning goal, out of service memory utilization, a data type indicator, a user identifier, and a slice name. For example, the processing module determines the DSN address range reassignment approach includes dividing encoded data slice storage burden of the out of service memory evenly between the two adjacent memories when the reassigning goal indicates to divide evenly and the adjacent memory free space is sufficient as compared to the out of service memory utilization (e.g., there is enough space).

The method continues at step 134 where the processing module re-assigns out of service memory DSN address range assignment in accordance with the DSN address range re-assignment approach. For example, the processing module re-assigns address range 101-250 to adjacent memory 1, address range 251-400 to adjacent memory 2, and no address range assignment to the out of service memory when the out of service memory DSN address range previous assignment was 201-300, adjacent memory 1 DSN address range previous assignment was 101-200, and adjacent memory 2 DSN address range previous assignment was to 301-400 when the DSN address range re-assignment approach is to split the out of service memory DSN address range assignment in half between the two adjacent memories.

The method continues at step 136 where the processing module facilitates rebuilding to populate the adjacent memories with encoded data slices that should have been stored in the out of service memory. For example, the processing module sends a rebuilding message to the storage integrity processing unit that includes the out of service memory DSN address range such that slice names within that address range are rebuilt and stored in the adjacent memories. As another example, the processing module rebuilds the encoded data slices by retrieving a threshold number of encoded data slices per encoded data slice set (e.g., slices of a data segment), dispersed storage error decode the threshold number of encoded data slices to produce a data segment, dispersed storage error encode the data segment to reproduce the encoded data slice set, and store the encoded data slice set in the adjacent memories in accordance with the DSN address range re-assignment approach and DSN address range assignments of each of the adjacent memories.

FIG. 7B is a flowchart illustrating an example of assigning a new memory that includes similar steps to FIG. 7A. The method begins with step 138 where a processing module (e.g., of a dispersed storage (DS) unit) identifies a new in-service memory. The identification may be based on one or more of an activated memory indicator, a memory insertion indicator, a maintenance schedule, a uptime schedule, a power-up schedule, a power savings indicator, a management input, an error rate history, a memory device type, a memory manufacturer indicator, a memory size indicator, and a bandwidth utilization indicator. For example, the processing module identifies the new in-service memory when the processing module receives the activated memory indicator. As another example, the processing module identifies the new in-service memory when the processing module receives an indication that bandwidth utilization may rise.

The method continues at step 140 where the processing module determines free space of associated memories. For example, the associated memories may include memories common to a dispersed storage (DS) unit. As another example, the associated memories may include memories of two DS units. The determination of free space may be based on one or more of a list, a message, a query, and a memory utilization table lookup. The method continues at step 142 where the processing module determines a memory pair migration score for each adjacent memory pair of the associated memories. The method continues with step 132 of FIG. 7A where the processing module determines a dispersed storage network (DSN) address range re-assignment approach. For example, the processing module determines the DSN address range re-assignment approach to migrate an equal number of slices from two of the associated memories to the new in-service memory. The method continues at step 146 where the processing module assigns the new in-service memory DSN address range assignment in accordance with the DSN address range re-assignment approach. For example, the processing module determines the DSN address range re-assignment to include equal number of address range re-assignments from a first associated memory and a second associated memory to the new in-service memory address range assignment.

The method continues at step 148 where the processing module migrates encoded data slices from at least one associated memory to the new in-service memory in accordance with the re-assigned approach. For example, the processing module migrates encoded data slices from the first associated memory to the new in-service memory and migrates encoded data slices from the second associated memory to the new in-service memory as previously discussed. The method continues at step 150 where the processing module updates at least one virtual DSN address to physical location table to match the reassigned address ranges (e.g., a local table, a DSN-wide table). For example, a slice name associated with an encoded data slice to migrate is associated with the new in-service memory and is disassociated with an out of service memory.

FIG. 8 is a flowchart illustrating another example of migrating encoded data slices, which includes similar steps to FIG. 7B. The method begins with step 152 where a processing module (e.g., of a dispersed storage (DS) processing unit) determines to migrate an encoded data slice from a memory to a second memory. The memory and the second memory may be included as memories of a dispersed storage (DS) unit. The processing module may determine to migrate a plurality of encoded data slices. The determination may be based on one or more of a migration score, a migration threshold, a memory free space indicator, a message, a predetermination, a failed memory indicator, and a new in-service memory indicator. For example, the processing module determines to migrate the encoded data slice from the memory to the second memory when the processing module determines that a migration score associated with the first and second memories is above a migration threshold.

The method continues at step 154 where the processing module determines memory dispersed storage network (DSN) address range assignment and second memory DSN address range assignment. The determination may be based on one or more of a number of encoded data slices to migrate, a system-wide virtual DSN address to physical location table lookup, a local virtual DSN to physical location table lookup, a message, and a list. For example, the processing module determines the memory DSN address range assignment and the second memory DSN address range assignment to move a boundary between the address ranges by one slice name corresponding to the encoded data slice to migrate.

The method continues at step 156 where the processing module selects an encoded data slice to migrate. For example, the encoded data slice to migrate may be a first encoded data slice to migrate of a plurality of encoded data slices. As another example, the encoded data slice to migrate may be a next encoded data slice to migrate of the plurality of encoded data slices. The method continues at step 158 where the processing module sends a read request message to a memory corresponding to the encoded data slice to migrate (e.g., including an associated slice name).

The method continues at step 160 where the processing module receives the encoded data slice to migrate. The method continues at step 162 where the processing module sends a write request message to the second memory that includes the encoded data slice to migrate and the associated slice name. The method continues at step 164 where the processing module sends a commit transaction request message and a finalize transaction request message to the second memory to facilitate storing the encoded data slice in the second memory. Alternatively, the processing module may send the commit transaction request message upon receiving a favorable write response message in response to the sending of the write request message to the second memory.

The method continues at step 166 where the processing module sends a delete request message to the memory that includes the slice name of the encoded data slice to migrate. Alternatively, the processing module may send the delete request message upon receiving a favorable commit transaction response message in response to sending the commit transaction request message to the second memory. The method continues at step 168 where the processing module sends a commit transaction request message and a finalize transaction request message to the memory to finish deleting the encoded data slice to migrate. Alternatively, the processing module sends the commit transaction request message upon receiving a favorable delete response message in response to sending of the delete request message to the memory. The method continues at step 150 of FIG. 7B where the processing module updates at least one virtual DSN address to physical location table (e.g., the slice name associated with the encoded data slice to migrate is moved from the address range of the memory to the address range of the second memory).

In addition, the processing module may form a virtual storage unit for the memory in the second memory such that read requests and write requests are coordinated while the migration of the encoded data slice is executed. In such a virtual store arrangement, simultaneous reads and writes to the memory and second memory may be prohibited to avoid synchronization issues. For instance, only one store slice request is executed at a time when two or more store slice requests are received for the memory and the second memory. As another instance, only one retrieve slice request is executed at a time when two or more retrieve slice requests are received for the memory and the second memory.

FIG. 9A is a flowchart illustrating an example of utilizing memory. The method begins with step 172 where a processing module (e.g., of a dispersed storage (DS) processing unit) receives a memory permit request (e.g., from a user device). A memory permit may be utilized to restrict utilization of a limited amount of local processing memory of a computing core as is discussed in greater detail with reference to FIGS. 9A-9C. A memory permit may include one or more of a user identifier, a data type indicator, an amount of memory requested indicator, an expected time duration, and a user device performance history indicator. The method continues at step 174 where the processing module determines current memory allocation. The current memory allocation may include one or more of a number of currently active permits, an amount of memory indicator allocated to currently active permits, an active memory utilization indicator, and an available memory indicator. The determination may be based on one or more of a permit table lookup, a predetermination, a list, a message, a user device query, and a DS unit query.

The method continues at step 176 where the processing module determines whether to grant the memory permit request. The determination may be based on one or more of the memory permit request, the current memory allocation, a maximum number of active permits threshold, a maximum amount of memory allocated to currently active permits threshold, an available memory threshold, and a DS unit performance history. For example, the processing module determines to grant the memory permit request when an amount of available memory is greater than an amount of memory requested and the number of active permits is less than the maximum number of active permits threshold. The method branches to the step where the processing module updates the current memory allocation when the processing module determines to grant the memory permit request. The method branches to step 180 when the processing module determines to grant the memory permit request. The method continues to step 178 when the processing module determines to not grant the memory permit request. The method continues at step 178 where the processing module sends a message. The message may include one or more of the memory permit request, a user identifier, an allowable amount of memory, and instructions to re-request. The processing module may send the message to a requesting entity. Alternatively, or in addition to, the processing module may send the message to a DS managing unit.

The method continues at step 180 where the processing module updates the current memory allocation when the processing module determines to grant the memory permit request. For example, the processing module increments the number of currently active permits indicator and updates the memory allocated to currently active permits indicator to include an amount of memory allocated. For example, the amount of memory allocated is substantially the same as the amount of memory requested. As another example, the amount of memory allocated is less than the amount of memory requested. The method continues at step 182 where the processing module sends a memory permit response message to the requesting entity. The memory permit response message may include one or more of user identity, the memory permit request, a memory permit identifier, the amount of memory allocated (e.g., granted), and a time duration of the memory permit. Data storage and retrieval methods utilizing the memory permit are discussed in greater detail with reference to FIGS. 9B-9C.

FIG. 9B is a flowchart illustrating an example of encoding data. The method begins with step 184 where a processing module (e.g., of a dispersed storage (DS) processing unit) receiving a data storage request (e.g., from a user device). The data storage request may include one or more of a memory permit identifier (ID), data, a user ID, a data size indicator, and a data type indicator. The method continues at step 186 where the processing module determines a memory permit associated with the data storage request. The determination may be based on one or more of the memory permit ID included in the data storage request, the user ID, a memory permit table lookup, and a message.

The method continues at step 188 where the processing module determines a system capability. The system capability may include one or more of available read/write bandwidth to dispersed storage (DS) units, available processing memory, available storage memory and a system loading indicator. The determination may be based on one or more of a performance history indicator, a test, a query, a message, and a list. For example, the processing module determines the available read/write bandwidth to DS units based on retrieving the performance history indicator from a local memory.

The method continues at step 190 where the processing module determines data storage parameters. The data storage parameters may include one or more of a slicing pillar width, a decode threshold, a number of write requests queued at once, a number of slices per write request, and a data segment size. The determination may be based on one or more of the memory permit, the system capability, a performance goal, available processing memory, a list, and a message. For example, the processing module determines a smaller data segment size when the processing module determines that the system capability is less than average.

The method continues at step 192 where the processing module dispersed storage error encodes data to produce encoded data slices in accordance with the data storage parameters. For example, the processing module encodes the data to produce a data segment size as determined by the data storage parameters to accommodate currently available processing memory and read/write bandwidth to the DS units. The method continues at step 194 where the processing module sends the encoded data slices to a dispersed storage network (DSN) memory in accordance with the data storage parameters for storage therein. For example, the processing module queues a small number of write requests messages to send to DS units of the DSN memory when the data storage parameters indicate a low number of write requests queued at once.

FIG. 9C is a flowchart illustrating an example of decoding encoded data slices, which include similar steps to FIG. 9B. The method begins with step 196 where a processing module (e.g., of a dispersed storage (DS) processing unit) receives a data retrieval request from a requesting entity (e.g., from a user device). The data retrieval request may include one or more of a memory permit identifier (ID), a user ID, a data size indicator, and a data type indicator. The method continues at step 198 where the processing module determines a memory permit associated with the data retrieval request. The determination may be based on one or more of the memory permit ID included in the data retrieval request, the user ID, a memory permit table lookup, and a message. The method continues at step 188 of FIG. 9B where the processing module determines a system capability.

The method continues at step 202 where the processing module determines data retrieval parameters. The data retrieval parameters may include one or more of a slicing pillar width, a decode threshold, a number of read requests queued at once, a number of slices per read request, how many data segments to reproduce once, and a data segment size. The determination may be based on one or more of the memory permit, the system capability, a performance goal, available processing memory, a list, and a message. For example, the processing module determines to simultaneously reproduce fewer data segments at once when the processing module determines that the system capability is less than average.

The method continues at step 204 where the processing module sends a plurality of read requests messages to a dispersed storage network (DSN) memory in accordance with the data retrieval parameters to retrieve a plurality of encoded data slices. For example, the processing module sends fewer simultaneous requests messages to DS units of the DSN memory when the data retrieval parameters indicate to simultaneously reproduce fewer data segments at once.

The method continues at step 206 where the processing module dispersed storage error decodes the plurality of encoded data slices to produce at least a portion of data in accordance with the data retrieval parameters. For example, the processing module decodes three sets of encoded data slices to reproduce three data segments as the data portion in accordance with the data retrieval parameters and system capability. The method continues at step 208 where the processing module sends the at least the portion of data to the requesting entity. The method may repeat to reproduce all portions of the data and to send all portions of the data to the requesting entity.

FIG. 10A is a flowchart illustrating an example of validating a request. The method begins with step 210 where the processing module (e.g., of a server, of a dispersed storage (DS) unit) receives a challenge request token from a requesting entity (e.g., a client, a user device). The challenge request token may include at least one of a client challenge and a client certificate chain, wherein the client certificate chain includes a client public key. The method continues at step 212 where the processing module determines whether the challenge request token is trusted. The processing module determines that the challenge request token is trusted when successfully matching at least one certificate authority identifier within the client certificate chain to a known certificate authority identifier (e.g., from a local known certificate authority list). The method branches to step 216 when the processing module determines that the challenge request token is trusted. The method continues to step 214 when the processing module determines that the challenge request token is not trusted. The method continues at step 214 where the processing module sends an error message indicating that the challenge process has failed. The processing module may send the error message to one or more of a user device, a requesting entity, and a DS managing unit.

The method continues at step 216 where the processing module sends a challenge response token when the processing module determines that the challenge request token is trusted. The challenge response token includes at least one of a server challenge, a server certificate chain, and a signature (e.g., a cryptographic hash utilizing an industry standards such as digital signature algorithm (DSA) or Rivest, Shamir, Adleman (RSA)) over the client challenge, the client certificate chain, the server challenge, and the server certificate chain utilizing a server private key (e.g., of a public key infrastructure (PKI) approach). The method continues at step 218 where the processing module receives a complete request token. The complete request token includes one or more of a client signature over the client challenge, the client certificate chain, the server challenge, and the server certificate chain.

The method continues at step 220 where the processing module determines whether the complete request token is valid. The processing module determines that the complete request token is valid when verifying the client signature utilizing the client public key received in the challenge request token. For example, the processing module compares a decrypted client signature, utilizing the client public key, to a calculated hash over the signature items and determines the client signature is valid when a comparison is substantially the same. The method branches to step 224 when the processing module determines that the complete request token is valid. The method continues to step 222 when the processing module determines that the complete request token is not valid. The method continues at step 214 where the processing module sends an error message. The method continues at step 224 where the processing module sends a complete response token when the processing module determines that the complete request token is valid. The complete response token includes an indicator that the request validation is successful.

FIG. 10B is a flowchart illustrating an example of producing a request, which include similar steps to FIG. 10A. The method begins with step 226 where a processing module (e.g., of a client, of a user device) sends a challenge request token to a server (e.g., a dispersed storage (DS) unit). The method continues at step 228 where the processing module receives a challenge response token. The method continues at step 230 where the processing module determines whether the challenge response token is trusted. The processing module determines that the challenge response token is trusted when successfully matching at least one certificate authority identifier within the server certificate chain to a known certificate authority identifier (e.g., from a local known certificate authority list). The method branches to step 234 when the processing module determines that the challenge response token is trusted. The method continues to step 214 of FIG. 10A when the processing module determines that the challenge response token is not trusted. The method continues with step 214 of FIG. 10A where the processing module sends an error message.

The method continues at step 234 where the processing module determines whether the challenge response token is valid when the processing module determines that the challenge response token is trusted. The processing module determines that the challenge response token is valid when verifying a server signature utilizing a server public key received in the challenge response token. For example, the processing module compares a decrypted server signature, utilizing the server public key, to a calculated hash over signature items and determines the server signature is valid when the comparison is substantially the same. The method branches to step 238 when the processing module determines that the challenge response token is valid. The method continues to step 214 of FIG. 10A when the processing module determines that the challenge response token is not valid. The method continues at step 214 of FIG. 10A where the processing module sends an error message.

The method continues at step 238 where the processing module sends a complete request token when the processing module determines that the challenge response token is valid. The method continues at step 240 where the processing module receives a complete response token. The messages previously discussed may be transmitted utilizing an industry standard protocol such as abstract syntax notation one (ASN.1).

As may be used herein, the terms “substantially” and “approximately” provides an industry-accepted tolerance for its corresponding term and/or relativity between items. Such an industry-accepted tolerance ranges from less than one percent to fifty percent and corresponds to, but is not limited to, component values, integrated circuit process variations, temperature variations, rise and fall times, and/or thermal noise. Such relativity between items ranges from a difference of a few percent to magnitude differences. As may also be used herein, the term(s) “operably coupled to”, “coupled to”, and/or “coupling” includes direct coupling between items and/or indirect coupling between items via an intervening item (e.g., an item includes, but is not limited to, a component, an element, a circuit, and/or a module) where, for indirect coupling, the intervening item does not modify the information of a signal but may adjust its current level, voltage level, and/or power level. As may further be used herein, inferred coupling (i.e., where one element is coupled to another element by inference) includes direct and indirect coupling between two items in the same manner as “coupled to”. As may even further be used herein, the term “operable to” or “operably coupled to” indicates that an item includes one or more of power connections, input(s), output(s), etc., to perform, when activated, one or more its corresponding functions and may further include inferred coupling to one or more other items. As may still further be used herein, the term “associated with”, includes direct and/or indirect coupling of separate items and/or one item being embedded within another item. As may be used herein, the term “compares favorably”, indicates that a comparison between two or more items, signals, etc., provides a desired relationship. For example, when the desired relationship is that signal 1 has a greater magnitude than signal 2, a favorable comparison may be achieved when the magnitude of signal 1 is greater than that of signal 2 or when the magnitude of signal 2 is less than that of signal 1.

As may also be used herein, the terms “processing module”, “processing circuit”, and/or “processing unit” may be a single processing device or a plurality of processing devices. Such a processing device may be a microprocessor, micro-controller, digital signal processor, microcomputer, central processing unit, field programmable gate array, programmable logic device, state machine, logic circuitry, analog circuitry, digital circuitry, and/or any device that manipulates signals (analog and/or digital) based on hard coding of the circuitry and/or operational instructions. The processing module, module, processing circuit, and/or processing unit may be, or further include, memory and/or an integrated memory element, which may be a single memory device, a plurality of memory devices, and/or embedded circuitry of another processing module, module, processing circuit, and/or processing unit. Such a memory device may be a read-only memory, random access memory, volatile memory, non-volatile memory, static memory, dynamic memory, flash memory, cache memory, and/or any device that stores digital information. Note that if the processing module, module, processing circuit, and/or processing unit includes more than one processing device, the processing devices may be centrally located (e.g., directly coupled together via a wired and/or wireless bus structure) or may be distributedly located (e.g., cloud computing via indirect coupling via a local area network and/or a wide area network). Further note that if the processing module, module, processing circuit, and/or processing unit implements one or more of its functions via a state machine, analog circuitry, digital circuitry, and/or logic circuitry, the memory and/or memory element storing the corresponding operational instructions may be embedded within, or external to, the circuitry comprising the state machine, analog circuitry, digital circuitry, and/or logic circuitry. Still further note that, the memory element may store, and the processing module, module, processing circuit, and/or processing unit executes, hard coded and/or operational instructions corresponding to at least some of the steps and/or functions illustrated in one or more of the Figures. Such a memory device or memory element can be included in an article of manufacture.

The present invention has been described above with the aid of method steps illustrating the performance of specified functions and relationships thereof. The boundaries and sequence of these functional building blocks and method steps have been arbitrarily defined herein for convenience of description. Alternate boundaries and sequences can be defined so long as the specified functions and relationships are appropriately performed. Any such alternate boundaries or sequences are thus within the scope and spirit of the claimed invention. Further, the boundaries of these functional building blocks have been arbitrarily defined for convenience of description. Alternate boundaries could be defined as long as the certain significant functions are appropriately performed. Similarly, flow diagram blocks may also have been arbitrarily defined herein to illustrate certain significant functionality. To the extent used, the flow diagram block boundaries and sequence could have been defined otherwise and still perform the certain significant functionality. Such alternate definitions of both functional building blocks and flow diagram blocks and sequences are thus within the scope and spirit of the claimed invention. One of average skill in the art will also recognize that the functional building blocks, and other illustrative blocks, modules and components herein, can be implemented as illustrated or by discrete components, application specific integrated circuits, processors executing appropriate software and the like or any combination thereof.

The present invention may have also been described, at least in part, in terms of one or more embodiments. An embodiment of the present invention is used herein to illustrate the present invention, an aspect thereof, a feature thereof, a concept thereof, and/or an example thereof. A physical embodiment of an apparatus, an article of manufacture, a machine, and/or of a process that embodies the present invention may include one or more of the aspects, features, concepts, examples, etc. described with reference to one or more of the embodiments discussed herein. Further, from figure to figure, the embodiments may incorporate the same or similarly named functions, steps, modules, etc. that may use the same or different reference numbers and, as such, the functions, steps, modules, etc. may be the same or similar functions, steps, modules, etc. or different ones.

While the transistors in the above described figure(s) is/are shown as field effect transistors (FETs), as one of ordinary skill in the art will appreciate, the transistors may be implemented using any type of transistor structure including, but not limited to, bipolar, metal oxide semiconductor field effect transistors (MOSFET), N-well transistors, P-well transistors, enhancement mode, depletion mode, and zero voltage threshold (VT) transistors.

Unless specifically stated to the contra, signals to, from, and/or between elements in a figure of any of the figures presented herein may be analog or digital, continuous time or discrete time, and single-ended or differential. For instance, if a signal path is shown as a single-ended path, it also represents a differential signal path. Similarly, if a signal path is shown as a differential path, it also represents a single-ended signal path. While one or more particular architectures are described herein, other architectures can likewise be implemented that use one or more data buses not expressly shown, direct connectivity between elements, and/or indirect coupling between other elements as recognized by one of average skill in the art.

The term “module” is used in the description of the various embodiments of the present invention. A module includes a processing module, a functional block, hardware, and/or software stored on memory for performing one or more functions as may be described herein. Note that, if the module is implemented via hardware, the hardware may operate independently and/or in conjunction software and/or firmware. As used herein, a module may contain one or more sub-modules, each of which may be one or more modules.

While particular combinations of various functions and features of the present invention have been expressly described herein, other combinations of these features and functions are likewise possible. The present invention is not limited by the particular examples disclosed herein and expressly incorporates these other combinations. 

1. A method comprises: storing a plurality of encoded data slices in a plurality of memory devices of a dispersed storage (DS) unit of a dispersed storage network (DSN) memory using a quantity load balancing function to substantially balance a quantity of encoded data slices stored within each of the plurality of memory devices, wherein data size of at least some of the plurality of encoded data slices is different; determining whether an available memory imbalance exists between a first memory device of the plurality of memory devices and a second memory device of the plurality of memory devices; and when the available memory imbalance exists, migrating one or more encoded data slices between the first and second memory devices to reduce the available memory imbalance.
 2. The method of claim 1, wherein the determining whether the available memory imbalance exists comprises: determining an available memory value of the first memory device; determining an available memory value of the second memory device; determining a difference available memory value based on the available memory values of the first and second memory device; comparing the difference available memory value with an available memory differential threshold; and when the comparing the difference available memory value with the available memory differential threshold is unfavorable, indicating that the available memory imbalance exists.
 3. The method of claim 2, wherein the determining the difference available memory value comprises at least one of: subtracting the available memory value of the first memory device from the available memory value of the second memory device to produce the difference available memory value; and calculating a migration score based on a subtraction of the available memory value of the first memory device from the available memory value of the second memory device to produce an available memory resultant value and dividing the available memory resultant value from one of the available memory value of the first memory device and the available memory value of the second memory device.
 4. The method of claim 1 further comprises: determining whether a second available memory imbalance exists between a third memory device of the plurality of memory devices and a fourth memory device of the plurality of memory devices; and when the second available memory imbalance exists, migrating another one or more encoded data slices between the third and fourth memory devices to reduce the available memory imbalance.
 5. The method of claim 4 further comprises: comparing the available memory imbalance with the second available memory imbalance; and prioritizing the migrating of the one or more encoded data slices between the first and second memory devices and the migrating of the other one or more encoded data slices between the third and fourth memory devices based on the comparing.
 6. The method of claim 1 further comprises: updating a slice location table based on the migrating the one or more encoded data slices between the first and second memory devices.
 7. The method of claim 1, wherein the migrating the one or more encoded data slices between the first and second memory devices comprises: when the available memory imbalance exists because an available memory value of the first memory device is less than an available memory value of the second memory device: selecting the one or more encoded data slices associated with the first memory for migration to produce a migration set of encoded data slices; retrieving the migration set of encoded data slices from the first memory device; storing the migration set of encoded data slices in the second memory device; modifying a first set of DSN addresses associated with the first memory device to produce a modified first set of DSN addresses; and modifying a second set of DSN addresses associated with the second memory device to produce a modified second set of DSN addresses.
 8. The method of claim 7, wherein the selecting the one or more encoded data slices comprises: determining a magnitude of the available memory imbalance; determining data size of the one or more encoded data slices; and selecting the one or more encoded data slices based on the magnitude of the available memory imbalance and the data size of the one or more encoded data slices.
 9. The method of claim 7, wherein the modifying the first set of DSN addresses to produce the modified first set of DSN addresses comprises: modifying the first set of DSN addresses to exclude DSN addresses associated with the migration set of encoded data slices.
 10. The method of claim 7, wherein the modifying the second set of DSN addresses to produce the modified second set of DSN addresses comprises: modifying the second set of DSN addresses to include DSN addresses associated with the migration set of encoded data slices.
 11. A dispersed storage (DS) unit of a dispersed storage network (DSN) memory comprises: an interface; a memory that includes a plurality of memory devices; and a processing module operable to: store a plurality of encoded data slices in the plurality of memory devices using a quantity load balancing function to substantially balance a quantity of encoded data slices stored within each of the plurality of memory devices, wherein data size of at least some of the plurality of encoded data slices is different; determine whether an available memory imbalance exists between a first memory device of the plurality of memory devices and a second memory device of the plurality of memory devices; and when the available memory imbalance exists, migrate one or more encoded data slices between the first and second memory devices to reduce the available memory imbalance.
 12. The DS unit of claim 11, wherein the processing module functions to determine whether the available memory imbalance exists by: determining an available memory value of the first memory device; determining an available memory value of the second memory device; determining a difference available memory value based on the available memory values of the first and second memory device; comparing the difference available memory value with an available memory differential threshold; and when the comparing the difference available memory value with the available memory differential threshold is unfavorable, indicating that the available memory imbalance exists.
 13. The DS unit of claim 12, wherein the processing module functions to determine the difference available memory value by at least one of: subtracting the available memory value of the first memory device from the available memory value of the second memory device to produce the difference available memory value; and calculating a migration score based on the subtraction of the available memory value of the first memory device from the available memory value of the second memory device to produce an available memory resultant value and dividing the available memory resultant value from one of the available memory value of the first memory device and the available memory value of the second memory device.
 14. The DS unit of claim 11, wherein the processing module further functions to: determine whether a second available memory imbalance exists between a third memory device of the plurality of memory devices and a fourth memory device of the plurality of memory devices; and when the second available memory imbalance exists, migrate another one or more encoded data slices between the third and fourth memory devices to reduce the available memory imbalance.
 15. The DS unit of claim 14, wherein the processing module further functions to: compare the available memory imbalance with the second available memory imbalance; and prioritize the migrating of the one or more encoded data slices between the first and second memory devices and the migrating of the other one or more encoded data slices between the third and fourth memory devices based on the comparing.
 16. The DS unit of claim 11, wherein the processing module further functions to: update a slice location table based on the migrating the one or more encoded data slices between the first and second memory devices.
 17. The DS unit of claim 11, wherein the processing module functions to migrate the one or more encoded data slices between the first and second memory devices by: when the available memory imbalance exists because an available memory value of the first memory device is less than an available memory value of the second memory device: selecting the one or more encoded data slices associated with the first memory for migration to produce a migration set of encoded data slices; retrieving the migration set of encoded data slices from the first memory; storing the migration set of encoded data slices in the second memory; modifying a first set of DSN addresses associated with the first memory device to produce a modified first set of DSN addresses; and modifying a second set of DSN addresses associated with the second memory device to produce a modified second set of DSN addresses.
 18. The DS unit of claim 17, wherein the processing module functions to select the one or more encoded data slices by: determining a magnitude of the available memory imbalance; determining data size of the one or more encoded data slices; and selecting the one or more encoded data slices based on the magnitude of the available memory imbalance and the data size of the one or more encoded data slices.
 19. The DS unit of claim 17, wherein the processing module functions to modify the first set of DSN addresses to produce the modified first set of DSN addresses by: modifying the first set of DSN addresses to exclude DSN addresses associated with the migration set of encoded data slices.
 20. The DS unit of claim 17, wherein the processing module functions to modify the second set of DSN addresses to produce the modified second set of DSN addresses by: modifying the second set of DSN addresses to include DSN addresses associated with the migration set of encoded data slices. 